Data Engineer

Role Overview

Data & Analytics Engineer for Aberdeen Advisors’ Digital Transformation Practice. This is a client-facing, hands-on data engineering role focused on building end-to-end data solutions—from raw ingestion to decision-ready visualizations.

Responsibilities

• Evaluate client data sources and design optimal ingestion strategies (APIs, connectors, direct exports).
• Build and structure data lakehouse tables using Medallion architecture (Bronze → Silver → Gold).
• Develop and validate transformation pipelines in Python/PySpark using Jupyter Notebooks.
• Apply ML where it adds value (e.g., forecasting, anomaly detection, narrative generation).
• Deliver dynamic dashboards in Power BI (preferred) or Tableau, validating visuals against source systems.
• Integrate LLM capabilities (OpenAI) for summaries, embeddings, and AI-generated narratives.
• Support agentic AI workflows as the practice scales.
• Communicate technical concepts clearly to non-technical stakeholders (CIOs and finance teams).

Requirements

• Strong Python fundamentals (write, read, and debug code confidently).
• Strong debugging and problem-solving instincts.
• Ability to communicate technical concepts clearly to stakeholders.
• Intellectual curiosity and willingness to learn in a fast-moving environment.

Nice to Have (Learnable on the Job)

• Data lake/lakehouse concepts (e.g., Delta tables, Microsoft Fabric, Databricks).
• Orchestration tools such as Airflow or Microsoft Fabric.
• Power BI or Tableau experience.
• ML fundamentals (classification, regression, clustering).
• LLM/API integration experience.
• Awareness of agentic AI frameworks and MCP tooling (e.g., Claude Code, VS Code agents).

Engagement Details

• Employment type: Full-Time Employee (FTE) or Contract (1099/C2C)
• Duration: 18-month+ engagements (FTE ongoing)
• Location: Fully remote (United States)
• Compensation: Commensurate with experience